With the increasing importance of data and artificial intelligence, organizations strive to become more data-driven. However, current data architectures are not necessarily designed to keep up with the scale and scope of data and analytics use cases. In fact, existing architectures often fail to deliver the promised value associated with them. Data mesh is a socio-technical concept that includes architectural aspects to promote data democratization and enables organizations to become truly data-driven. As the concept of data mesh is still novel, it lacks empirical insights from the field. Specifically, an understanding of the motivational factors for introducing data mesh, the associated challenges, best practices, its business impact, and potential archetypes, is missing. To address this gap, we conduct 15 semi-structured interviews with industry experts. Our results show, among other insights, that industry experts have difficulties with the transition toward federated governance associated with the data mesh concept, the shift of responsibility for the development, provision, and maintenance of data products, and the concept of a data product model. In our work, we derive multiple best practices and suggest organizations embrace elements of data fabric, observe the data product usage, create quick wins in the early phases, and favor small dedicated teams that prioritize data products. While we acknowledge that organizations need to apply best practices according to their individual needs, we also deduct two archetypes that provide suggestions in more detail. Our findings synthesize insights from industry experts and provide researchers and professionals with guidelines for the successful adoption of data mesh.

翻译：随着数据与人工智能重要性的日益提升，组织正致力于成为数据驱动型企业。然而，当前的数据架构未必能够跟上数据与分析应用场景的规模化发展需求。事实上，现有架构往往无法兑现其承诺的价值。数据网格是一种包含架构层面的社会技术概念，旨在促进数据民主化，助力组织真正实现数据驱动转型。由于数据网格概念仍属新兴领域，尚缺乏来自实践的经验性见解，尤其是缺乏对其引入动机、相关挑战、最佳实践、商业影响及潜在典型模式的系统性认知。为填补这一空白，我们与业界专家开展了15次半结构化访谈。研究结果表明：业界专家在向数据网格概念相关的联邦治理转型、开发/提供/维护数据产品的职责转移、以及数据产品模型概念等方面面临困境。本研究提炼出多项最佳实践，建议组织采纳数据织网要素、监测数据产品使用情况、在初期阶段打造速赢成果，并优先组建专注于数据产品的小型专业团队。虽然我们认同组织需根据自身需求应用最佳实践，但同时也归纳出两种提供更细致建议的典型模式。本研究成果综合了业界专家的实践洞见，为研究人员与从业者提供了成功采纳数据网格的实施指南。